Your question is Vector DB Indexing Trade-offs. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
Explain the tradeoffs between different vector database indexing strategies for large-scale embeddings.
Discuss at least HNSW, IVF, product quantization, and disk-based or graph-based approaches. Compare recall, query latency, memory footprint, ingestion and rebuild cost, filtering behavior, update patterns, and operational complexity. Describe how you would benchmark the alternatives and choose an index for a production RAG workload.
